اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدRedshift-space streaming velocity effects on the Lyman-$alpha$ forest baryon acoustic oscillation scale
119
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
The baryon acoustic oscillation (BAO) scale acts as a standard ruler for measuring cosmological distances and has therefore emerged as a leading probe of cosmic expansion history. However, any physical effect that alters the length of the ruler can lead to a bias in our determination of distance and expansion rate. One of these physical effects is the streaming velocity, the relative velocity between baryons and dark matter in the early Universe, which couples to the BAO scale due to their common origin in acoustic waves at recombination. In this work, we investigate the impact of streaming velocity on the BAO feature of the Lyman-$alpha$ forest auto-power spectrum, one of the main tracers being used by the recently commissioned DESI spectrograph. To do this, we develop a new perturbative model for Lyman-$alpha$ flux density contrast which is complete to second order for a certain set of fields, and applicable to any redshift-space tracer of structure since it is based only on symmetry considerations. We find that there are 8 biasing coefficients through second order. We find streaming velocity-induced shifts in the BAO scale of 0.081--0.149% (transverse direction) and 0.053--0.058% (radial direction), depending on the model for the biasing coefficients used. These are smaller than, but not negligible compared to, the DESI Lyman-$alpha$ BAO error budget, which is 0.46% on the overall scale. The sensitivity of these results to our choice of bias parameters underscores the need for future work to measure the higher-order biasing coefficients from simulations, especially for future experiments beyond DESI.
قيم البحث
اقرأ أيضاً
The relative velocity between baryons and dark matter in the early Universe can suppress the formation of small-scale baryonic structure and leave an imprint on the baryon acoustic oscillation (BAO) scale at low redshifts after reionization. This str
eaming velocity affects the post-reionization gas distribution by directly reducing the abundance of pre-existing mini-halos ($lesssim 10^7 M_{bigodot}$) that could be destroyed by reionization and indirectly modulating reionization history via photoionization within these mini-halos. In this work, we investigate the effect of streaming velocity on the BAO feature in HI 21 cm intensity mapping after reionization, with a focus on redshifts $3.5lesssim zlesssim5.5$. We build a spatially modulated halo model that includes the dependence of the filtering mass on the local reionization redshift and thermal history of the intergalactic gas. In our fiducial model, we find isotropic streaming velocity bias coefficients $b_v$ ranging from $-0.0033$ at $z=3.5$ to $-0.0248$ at $z=5.5$, which indicates that the BAO scale is stretched (i.e., the peaks shift to lower $k$). In particular, streaming velocity shifts the transverse BAO scale between 0.087% ($z=3.5$) and 0.37% ($z=5.5$) and shifts the radial BAO scale between 0.13% ($z=3.5$) and 0.52% ($z=5.5$). These shifts exceed the projected error bars from the more ambitious proposed hemispherical-scale surveys in HI (0.13% at $1sigma$ per $Delta z = 0.5$ bin).
This work presents a new physically-motivated supervised machine learning method, Hydro-BAM, to reproduce the three-dimensional Lyman-$alpha$ forest field in real and in redshift space learning from a reference hydrodynamic simulation, thereby saving
about 7 orders of magnitude in computing time. We show that our method is accurate up to $ksim1,h,rm{Mpc}^{-1}$ in the one- (PDF), two- (power-spectra) and three-point (bi-spectra) statistics of the reconstructed fields. When compared to the reference simulation including redshift space distortions, our method achieves deviations of $lesssim2%$ up to $k=0.6,h,rm{Mpc}^{-1}$ in the monopole, $lesssim5%$ up to $k=0.9,h,rm{Mpc}^{-1}$ in the quadrupole. The bi-spectrum is well reproduced for triangle configurations with sides up to $k=0.8,h,rm{Mpc}^{-1}$. In contrast, the commonly-adopted Fluctuating Gunn-Peterson approximation shows significant deviations already neglecting peculiar motions at configurations with sides of $k=0.2-0.4,h,rm{Mpc}^{-1}$ in the bi-spectrum, being also significantly less accurate in the power-spectrum (within 5$%$ up to $k=0.7,h,rm{Mpc}^{-1}$). We conclude that an accurate analysis of the Lyman-$alpha$ forest requires considering the complex baryonic thermodynamical large-scale structure relations. Our hierarchical domain specific machine learning method can efficiently exploit this and is ready to generate accurate Lyman-$alpha$ forest mock catalogues covering large volumes required by surveys such as DESI and WEAVE.
In recent years, the autocorrelation of the hydrogen Lyman-{alpha} forest has been used to observe the baryon acoustic peak at redshift 2 < z < 3.5 using tens of thousands of QSO spectra from the BOSS survey. However, the interstellar medium of the M
ilky-Way introduces absorption lines into the spectrum of any extragalactic source. These lines, while weak and undetectable in a single BOSS spectrum, could potentially bias the cosmological signal. In order to examine this, we generate absorption line maps by stacking over a million spectra of galaxies and QSOs. We find that the systematics introduced are too small to affect the current accuracy of the baryon acoustic peak, but might be relevant to future surveys such as the Dark Energy Spectroscopic Instrument (DESI). We outline a method to account for this with future datasets.
We present a measurement of baryonic acoustic oscillations (BAO) from Lyman-$alpha$ (Ly$alpha$) absorption and quasars at an effective redshift $z=2.33$ using the complete extended Baryonic Oscillation Spectroscopic Survey (eBOSS). The sixteenth and
final eBOSS data release (SDSS DR16) contains all data from eBOSS and its predecessor, the Baryonic Oscillation Spectroscopic Survey (BOSS), providing $210,005$ quasars with $z_{q}>2.10$ that are used to measure Ly$alpha$ absorption. We measure the BAO scale both in the auto-correlation of Ly$alpha$ absorption and in its cross correlation with $341,468$ quasars with redshift $z_{q}>1.77$. Apart from the statistical gain from new quasars and deeper observations, the main improvements over previous work come from more accurate modeling of physical and instrumental correlations and the use of new sets of mock data. Combining the BAO measurement from the auto- and cross-correlation yields the constraints of the two ratios $D_{H}(z=2.33)/r_{d} = 8.99 pm 0.19$ and $D_{M}(z=2.33)/r_{d} = 37.5 pm 1.1$, where the error bars are statistical. These results are within $1.5sigma$ of the prediction of the flat-$Lambda$CDM cosmology of Planck~(2016). The analysis code, texttt{picca}, the catalog of the flux-transmission field measurements, and the $Delta chi^{2}$ surfaces are publicly available.
We describe mock data-sets generated to simulate the high-redshift quasar sample in Data Release 11 (DR11) of the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS). The mock spectra contain Ly{alpha} forest correlations useful for studying the
3D correlation function including Baryon Acoustic Oscillations (BAO). They also include astrophysical effects such as quasar continuum diversity and high-density absorbers, instrumental effects such as noise and spectral resolution, as well as imperfections introduced by the SDSS pipeline treatment of the raw data. The Ly{alpha} forest BAO analysis of the BOSS collaboration, described in Delubac et al. 2014, has used these mock data-sets to develop and cross-check analysis procedures prior to performing the BAO analysis on real data, and for continued systematic cross checks. Tests presented here show that the simulations reproduce sufficiently well important characteristics of real spectra. These mock data-sets will be made available together with the data at the time of the Data Release 11.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
